Category Archives: Financial Metrics

Term Sheets: Landmines and Ticking Time Bombs!

Wall Street is the only place that people ride to in a Rolls Royce to get advice from those who take the subway. – Warren Buffett

are u ready

So the big day is here. You have evangelized your product across various circles and the good news is that a VC has stepped forward to invest in your company. So the hard work is all done! You can rest on your laurels, sign the term sheet that the VC has pushed across the table, and execute the sheet, trigger the stock purchase, voter and investor rights agreements, get the wire and you are up and running! Wait … sounds too good to be true, doesn’t it? And yes you are right! If only things were that easy. The devil is in the details. So let us go over some of the details that you need to watch out for.

1. First, term sheet does not trigger the wire. Signing a term sheet does not mean that the VC will invest in your company. The road is still long and treacherous.  All the term sheet does is that it requires you to keep silent on the negotiations, and may even prevent you to shop the deal to anyone else.  The key investment terms are laid out in the sheet and would be used in much greater detail when the stock purchase agreement, the investor rights agreement, the voting agreement and other documents are crafted.

landmines2. Make sure that you have an attorney representing you. And more importantly, an attorney that has experience in the field and has reviewed a lot of such documents. As noted, the devil is in the details. A little “and” or “or” can put you back significantly. But it is just as important for you to know some of the key elements that govern an investment agreement. You can quiz your attorney on these because some of these are important enough to impact your operating degree of freedom in the company.The starting point of a term sheet is valuation of the company. You will hear the concept of pre-money valuation vs. post-money valuation. It is quite simple.  The Pre-Money Valuation + Investment = Post-Money Valuation. In other words, Pre-money valuation refers to the value of a company not including external funding or the latest round of funding. Post-Money thus includes the pre-money plus the incremental injection of capital. Let us look at an example:

Let’s explain the difference by using an example. Suppose that an investor is looking to invest in a start up. Both parties agree that the company is worth $1 million and the investor will put in $250,000.

The ownership percentages will depend on whether this is a $1 million pre-money or post-money valuation. If the $1 million valuation is pre-money, the company is valued at $1 million before the investment and after investment will be valued at $1.25 million. If the $1 million valuation takes into consideration the $250,000 investment, it is referred to as post-money.  Thus in a pre-money valuation, the Investor owns 20%. Why? The total valuation is $1.25M which is $1M pre-money + $250K capital. So the math translates to $250K/$1,250K = 20%.  If the investor says that they will value company $1M post-money, what they are saying is that they are actually giving you a pre-money valuation of $750K. In other words, they will own 25% of the company rather than 20%. Your ownership rights go down by 5% which, for all intents and purposes, is significant.

3. When a round of financing is done, security is exchanged in lieu of cash received. You already have common stock but these are not the securities being exchanged. The company would issue preferred stock. Preferred stock comes with certain rights, preferences, privileges and covenants. Compared to common stock, it is a superior security. There are a number of important rights and privileges that investors secure via a preferred stock purchase, including a right to a board seat, information rights, a right to participate in future rounds to protect their ownership percentage (called a pro-rata right), a right to purchase any common stock that might come onto the market (called a right of first refusal), a right to participate alongside any common stock that might get sold (called a co-sale right), and an adjustment in the purchase price to reflect sales of stock at lower prices (called an anti-dilution right).  Let us examine this in greater detail now. There are two types of preferred. The regular vanilla Convertible Preferred and the Participating Preferred. As the latter name suggests, the Participating Preferred allows the VC to receive back their invested capital and the cumulative dividends, if any before common stockholders (that is you), but also enables them to participate on an as-converted basis in the returns to you, the common stockholder.  Here is the math:Let us say company raises $3M at a $3M pre-money valuation. As mentioned before in point (3), the stake is 50%-50% owner-investor.

Let us say company sells for $25M. Now the investor has participating preferred or convertible preferred. How does the difference impact you, the stockholder or the founder. Here goes!

i.      Participating Preferred. Investor gets their $3M back. There is still $22M left in the coffers. Investor splits 50-50 based on their participating preferred. You and Investor both take home $11M from the residual pool. Investor has $14M, and you have $11M. Congrats!

ii.      Convertible Preferred. Investor gets 50% or $12.5M and you get the same – $12.5M. In other words, convertible preferred just got you a few more drinks at the bar. Hearty Congratulations!

Bear in mind that if the Exit Value is lower, the difference becomes more meaningful. Let us say exit was $10M. The Preferred participant gets $3M + $3.5M = $6.5M while you end up with $3.5M.

bombs4. One of the key provisions is Liquidation Preferences. It can be a ticking time bomb. Careful! Some investors may sometimes ask for a multiple of their investment as a preference. This provision provides downside protection to investors. In the event of liquidation, the company has to pay back the capital injected for preferred. This would mean a 1X liquidation preference. However, you can have a 2X liquidation preference which means the investor will get back twice as much as what they injected. Most liquidation preferences range from 1X to 2X, although you can have higher liquidation preference multiples as well. However, bear in mind that this becomes important only when the company is forced to liquidate and sell of their assets. If all is gung-ho, this is a silent clause and no sweat off your brow.

5. Redemption rights. The right of redemption is the right to demand under certain conditions that the company buys back its own shares from its investors at a fixed price. This right may be included to require a company to buy back its shares if there has not been an exit within a pre-determined period. Failure to redeem shares when requested might result in the investors gaining improved rights, such as enhanced voting rights.

6. The terms could demand that a certain option pool or a pot of stock is kept aside for existing and future employees, or other service providers. It could be a range anywhere between 10-20% of the total stock. When you reserve this pool, you are cutting into your ownership stake. In those instances when you have series of financings and each financing requires you to set aside a small pool, it dilutes you and your previous investors.  In general, the way these pools are structured is to give you some headroom up to at least 24 months to accommodate employee growth and providing them incentives. The pool only becomes smaller with the passage of time.

7. Another term is the Anti-Dilution Provision.  In its simplest form, anti-dilution rights are a zero- sum game. No one has an advantage over the other. However, this becomes important only when there is a down round.  A down round basically means that the company is valued lower in subsequent financing than previously. A company valued at $25M in Series A and $15M in Series B – the Series B would be considered a down round.  Two Types of Anti-Dilution:

Full ratchet Anti-Dilution: If the new stock is priced lower than prior stock, the early investor has a clause to convert their shares to the new price. For example, if prior investor paid $1.00 and then it was reset in a later round to $0.50, then the prior investors will have 2X rights to common stock. In other words, you are hit with major dilution as are the later investors. This clause is a big hurdle for new investors.

Weighted Average Anti-Dilution. Old investor’s share is adjusted in proportion to the dilution impact of a down round

8. Pay to Play. These are clauses that work in your, the Company, favor. Basically, investors have to invest some money in later financings, and if they do not – their rights may be reduced.  However, having these clauses may put your mind at ease, but may create problems in terms of syndicating or getting investments. Some investors are reluctant to put their money in when there are pay to play clauses in the agreement.

9. Right of First Refusal. A company has no obligation to sell stock in future financing rounds to existing investors. Some investors would like to participate and may seek pro-rata participating to keep their ownership stake the same post-financing. Some investors may even want super pro-rata rights which means that they be allowed to participate to such an extent that their new ownership in the company is greater than their previous ownership stake.

10. Board of Directors. A large board creates complexity. Preferable to have a small but strategic board. New investors will require some representation. If too many investors request representation, the Company may have smaller internal representatives and may be outvoted on certain issues. Be aware of the dynamics of a mushrooming board!

11.Voting Rights. Investors may request certain veto authority or have rights to vote in favor of or against a corporate initiative.  Company founders may want super-voting rights to exercise greater control. These matters are delicate and going one way or the other may cause personal issues among the participants. However, these matters can be easily resolved by essentially having carve-outs that spell out rights and encumbrances.

12.Drag Along Provision. Might create an obligation on all shareholders of the company to sell their shares to a potential purchaser if a certain percentage of the shareholders (or of a specific class of shareholders) votes to sell to that purchaser. Often in early rounds drag along rights can only be enforced with the consent of those holding at least a majority of the shares held by investors. These rights can be useful in the context of a sale where potential purchasers will want to acquire 100% of the shares of the company in order to avoid having responsibilities to minority shareholders after the acquisition. Many jurisdictions provide for such a process, usually when a third party has acquired at least 90% of the shares.

13.Representations and Warranties. Venture capital investors expect appropriate representations and warranties to be provided by key founders, management and the company. The primary purpose of the representations and warranties is to provide the investors with a complete and accurate understanding of the current condition of the company and its past history so that the investors can evaluate the risks of investing in the company prior to subscribing for their shares. The representations and warranties will typically cover areas such as the legal existence of the company (including all share capital details), the company’s financial statements, the business plan, asset ownership (in particular intellectual property rights), liabilities (contingent or otherwise), material contracts, employees and litigation. It is very rare that a company is in a perfect state. The warrantors have the opportunity to set out issues which ought to be brought to the attention of the new investors through a disclosure letter or schedule of exceptions. This is usually provided by the warrantors and discloses detailed information concerning any exceptions to or carve-outs from the representations and warranties. If a matter is referred to in the disclosure letter the investors are deemed to have notice of it and will not be able to claim for breach of warranty in respect of that matter. Investors expect those providing representations and warranties about the company to reimburse the investors for the diminution in share value attributable to the representations and warranties being inaccurate or if there are exceptions to them that have not been fully disclosed. There are usually limits to the exposure of the warrantors (i.e. a dollar cap on the amount that can be recovered from individual warrantors). These are matters for negotiation when documentation is being finalized. The limits may vary according to the severity of the breach, the size of the investment and the financial resources of the warrantors. The limits which typically apply to founders are lower than for the company itself (where the company limit will typically be the sum invested or that sum plus a minimum return).

14. Information Rights. In order for venture capital investors to monitor the condition of their investment, it is essential that the company provides them with certain regular updates concerning its financial condition and budgets, as well as a general right to visit the company and examine its books and records. This sometimes includes direct access to the company’s auditors and bankers. These contractually defined obligations typically include timely transmittal of annual financial statements (including audit requirements, if applicable), annual budgets, and audited monthly and quarterly financial statements.

15. Exit. Venture capital investors want to see a path from their investment in the company leading to an exit, most often in the form of a disposal of their shares following an IPO or by participating in a sale. Sometimes the threshold for a liquidity event or will be a qualified exit. If used, it will mean that a liquidity event will only occur, and conversion of preferred shares will only be compulsory, if an IPO falls within the definition of a qualified exit. A qualified exit is usually defined as a sale or IPO on a recognized investment exchange which, in either case, is of a certain value to ensure the investors get a minimum return on their investment. Consequently, investors usually require undertakings from the company and other shareholders that they will endeavor to achieve an appropriate share listing or trade sale within a limited period of time (typically anywhere between 3 and 7 years depending on the stage of investment and the maturity of the company). If such an exit is not achieved, investors often build in structures which will allow them to withdraw some or the entire amount of their investment.

16. Non-Compete, Confidentiality Agreements. It is good practice for any company to have certain types of agreements in place with its employees. For technology start-ups, these generally include Confidentiality Agreements (to protect against loss of company trade secrets, know-how, customer lists, and other potentially sensitive information), Intellectual Property Assignment Agreements (to ensure that intellectual property developed by academic institutions or by employees before they were employed by the company will belong to the company) and Employment Contracts or Consultancy Agreements (which will include provisions to ensure that all intellectual property developed by a company’s employees belongs to the company). Where the company is a spin-out from an academic institution, the founders will frequently be consultants of the company and continue to be employees of the academic institution, at least until the company is more established. Investors also seek to have key founders and managers enter into Non-compete Agreements with the company. In most cases, the investment in the company is based largely on the value of the technology and management experience of the management team and founders. If they were to leave the company to create or work for a competitor, this could significantly affect the company’s value. Investors normally require that these agreements be included in the Investment Agreement as well as in the Employment/Consultancy Agreements with the founders and senior managers, to enable them to have a right of direct action against the founders’ and managers if the restrictions are breached.

vc process

Disseminating financial knowledge to develop engaged organizations

Financial awareness of key drivers are becoming the paramount leading indicators for organizational success. For most, the finance department is a corner office service that offers ad hoc analysis on strategic and operational initiatives to a company, and provides an ex-post assessment of the financial condition of the company among a select few. There are some key financial metrics that one wants to measure across all companies and all industries without exception, but then there are unique metrics that reflect the key underlying drivers for organizational success. Organizations align their forays into new markets, new strategies and new ventures around a narrative that culminates in a financial metric or a proxy that illustrates opportunities lost or gained.

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Having been cast in operational finance roles for a good length of my career, I have often encountered a high level of interest to learn financial concepts in areas such as engineering, product management, operations, sales, etc. I have to admit that I have been humbled by the fairly wide common-sense understanding of basic financial concepts that these folks have. However, in most cases, the understanding is less than skin deep with misunderstandings that are meaningful. The good news is that I have also noticed a promising trend, namely … the questions are more thoroughly weighed by the “non-finance” participants, and there seems to be an elevated understanding of key financial drivers that translate to commercial success. This knowledge continues to accelerate … largely, because of convergence of areas around data science, analytics, assessment of personal ownership stakes, etc. But the passing of such information across these channels to the hungry recipients are not formalized. In other words, I posit that having a formal channel of inculcating financial education across the various functional areas would pay rich dividends for the company in the long run. Finance is a vast enough field that partaking general knowledge in these concepts which are more than merely skin-deep would also enable the finance group to engage in meaningful conversations with other functional experts, thus allowing the narrative around the numbers to be more wholesome. Thus, imparting the financial knowledge would be beneficial to the finance department as well.

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To be effective in creating a formal channel of disseminating information of the key areas in finance that matter to the organization, it is important to understand the operational drivers. When I say operational drivers, I am expanding that to encompass drivers that may uniquely affect other functional areas. For example, sales may be concerned with revenue, margins whereas production may be concerned with server capacity, work-in-process and throughput, etc. At the end, the financial metrics are derivatives. They are cross products of single or multiple drivers and these are the elements that need to be fleshed out to effect a spirited conversation. That would then enable the production of a financial barometer that everyone in the organization can rally behind and understand, and more importantly … be able to assess how their individual contribution has and will advance organization goals.

The Big Data Movement: Importance and Relevance today?

We are entering into a new age wherein we are interested in picking up a finer understanding of relationships between businesses and customers, organizations and employees, products and how they are being used,  how different aspects of the business and the organizations connect to produce meaningful and actionable relevant information, etc. We are seeing a lot of data, and the old tools to manage, process and gather insights from the data like spreadsheets, SQL databases, etc., are not scalable to current needs. Thus, Big Data is becoming a framework to approach how to process, store and cope with the reams of data that is being collected.

According to IDC, it is imperative that organizations and IT leaders focus on the ever-increasing volume, variety and velocity of information that forms big data.

  • Volume. Many factors contribute to the increase in data volume – transaction-based data stored through the years, text data constantly streaming in from social media, increasing amounts of sensor data being collected, etc. In the past, excessive data volume created a storage issue. But with today’s decreasing storage costs, other issues emerge, including how to determine relevance amidst the large volumes of data and how to create value from data that is relevant.
  • Variety. Data today comes in all types of formats – from traditional databases to hierarchical data stores created by end users and OLAP systems, to text documents, email, meter-collected data, video, audio, stock ticker data and financial transactions. By some estimates, 80 percent of an organization’s data is not numeric! But it still must be included in analyses and decision making.
  • Velocity. According to Gartner, velocity “means both how fast data is being produced and how fast the data must be processed to meet demand.” RFID tags and smart metering are driving an increasing need to deal with torrents of data in near-real time. Reacting quickly enough to deal with velocity is a challenge to most organizations.

SAS has added two additional dimensions:

  • Variability. In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something big trending in the social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage – especially with social media involved.
  • Complexity. When you deal with huge volumes of data, it comes from multiple sources. It is quite an undertaking to link, match, cleanse and transform data across systems. However, it is necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control. Data governance can help you determine how disparate data relates to common definitions and how to systematically integrate structured and unstructured data assets to produce high-quality information that is useful, appropriate and up-to-date.

 

So to reiterate, Big Data is a framework stemming from the realization that the data has gathered significant pace and that it’s growth has exceeded the capacity for an organization to handle, store and analyze the data in a manner that offers meaningful insights into the relationships between data points.  I am calling this a framework, unlike other materials that call Big Data a consequent of the inability of organizations to handle mass amounts of data. I refer to Big Data as a framework because it sets the parameters around an organizations’ decision as to when and which tools must be deployed to address the data scalability issues.

Thus to put the appropriate parameters around when an organization must consider Big Data as part of their analytics roadmap in order to understand the patterns of data better, they have to answer the following  ten questions:

  1. What are the different types of data that should be gathered?
  2. What are the mechanisms that have to be deployed to gather the relevant data?
  3. How should the data be processed, transformed and stored?
  4. How do we ensure that there is no single point of failure in data storage and data loss that may compromise data integrity?
  5. What are the models that have to be used to analyze the data?
  6. How are the findings of the data to be distributed to relevant parties?
  7. How do we assure the security of the data that will be distributed?
  8. What mechanisms do we create to implement feedback against the data to preserve data integrity?
  9. How do we morph the big data model into new forms that accounts for new patterns to reflect what is meaningful and actionable?
  10. How do we create a learning path for the big data model framework?

Some of the existing literature have commingled Big Data framework with analytics. In fact, the literature has gone on to make a rather assertive statement i.e. that Big Data and predictive analytics be looked upon in the same vein. Nothing could be further from the truth!

There are several tools available in the market to do predictive analytics against a set of data that may not qualify for the Big Data framework. While I was the CFO at Atari, we deployed business intelligence tools using Microstrategy, and Microstrategy had predictive modules. In my recent past, we had explored SAS and Minitab tools to do predictive analytics. In fact, even Excel can do multivariate, ANOVA and regressions analysis and best curve fit analysis. These analytical techniques have been part of the analytics arsenal for a long time. Different data sizes may need different tools to instantiate relevant predictive analysis. This is a very important point because companies that do not have Big Data ought to seriously reconsider their strategy of what tools and frameworks to use to gather insights. I have known companies that have gone the Big Data route, although all data points ( excuse my pun), even after incorporating capacity and forecasts, suggest that alternative tools are more cost-effective than implementing Big Data solutions. Big Data is not a one-size fit-all model. It is an expensive implementation. However, for the right data size which in this case would be very large data size, Big Data implementation would be extremely beneficial and cost effective in terms of the total cost of ownership.

Areas where Big Data Framework can be applied!

Some areas lend themselves to the application of the Big Data Framework.  I have identified broadly four key areas:

  1. Marketing and Sales: Consumer behavior, marketing campaigns, sales pipelines, conversions, marketing funnels and drop-offs, distribution channels are all areas where Big Data can be applied to gather deeper insights.
  2. Human Resources: Employee engagement, employee hiring, employee retention, organization knowledge base, impact of cross-functional training, reviews, compensation plans are elements that Big Data can surface. After all, generally over 60% of company resources are invested in HR.
  3. Production and Operational Environments: Data growth, different types of data appended as the business learns about the consumer, concurrent usage patterns, traffic, web analytics are prime examples.
  4. Financial Planning and Business Operational Analytics:  Predictive analytics around bottoms-up sales, marketing campaigns ROI, customer acquisitions costs, earned media and paid media, margins by SKU’s and distribution channels, operational expenses, portfolio evaluation, risk analysis, etc., are some of the examples in this category.

Hadoop: A Small Note!

Hadoop is becoming a more widely accepted tool in addressing Big Data Needs.  It was invented by Google so they could index the structural and text information that they were collecting and present meaningful and actionable results to the users quickly. It was further developed by Yahoo that tweaked Hadoop for enterprise applications.

Hadoop runs on a large number of machines that don’t share memory or disks. The Hadoop software runs on each of these machines. Thus, if you have for example – over 10 gigabytes of data – you take that data and spread that across different machines.  Hadoop tracks where all these data resides! The servers or machines are called nodes, and the common logical categories around which the data is disseminated are called clusters.  Thus each server operates on its own little piece of the data, and then once the data is processed, the results are delivered to the main client as a unified whole. The method of reducing the disparate sources of information residing in various nodes and clusters into one unified whole is the process of MapReduce, an important mechanism of Hadoop. You will also hear something called Hive which is nothing but a data warehouse. This could be a structured or unstructured warehouse upon which the Hadoop works upon, processes data, enables redundancy across the clusters and offers a unified solution through the MapReduce function.

Personally, I have always been interested in Business Intelligence. I have always considered BI as a stepping stone, in the new age, to be a handy tool to truly understand a business and develop financial and operational models that are fairly close to the trending insights that the data generates.  So my ear is always to the ground as I follow the developments in this area … and though I have not implemented a Big Data solution, I have always been and will continue to be interested in seeing its applications in certain contexts and against the various use cases in organizations.

 

Implementing Balanced Scorecard Model for Employee Engagement

The Balanced Scorecard Model (BSC) was introduced by Kaplan & Norton in their book “The Balanced Scorecard” (1996). It is one of the more widely used management tools in large organizations.

One of the major strengths of the BSC model is how the key categories in the BSC model links to corporate missions and objectives. The key categories which are referred to as “perspectives” illustrated in the BSC model are:

Financial Perspective:

Kaplan and Norton do not disregard the traditional need for financial data. Timely and accurate data will always be a priority, and managers will do whatever necessary to provide it. In fact, often there is more than enough handling and processing of financial data. With the implementation of a corporate database, it is hoped that more of the processing can be centralized and automated. But the point is that the current emphasis on financials leads to the “unbalanced” situation with regard to other perspectives. There is perhaps a need to include additional financial-related data, such as risk assessment and cost-benefit data, in this category.

Customer Perspective

Recent management philosophy has shown an increasing realization of the importance of customer focus and customer satisfaction in any business. These are leading indicators: if customers are not satisfied, they will eventually find other suppliers that will meet their needs. Poor performance from this perspective is thus a leading indicator of future decline, even though the current financial picture may look good. In developing metrics for satisfaction, customers should be analyzed in terms of kinds of customers and the kinds of processes for which we are providing a product or service to those customer groups

Internal Business Process Perspective

This perspective refers to internal business processes. Metrics based on this perspective allow the managers to know how well their business is running, and whether its products and services conform to customer requirements (the mission). These metrics have to be carefully designed by those who know these processes most intimately; with our unique missions these are not necessarily something that can be developed by outside consultants. My personal opinion on this matter is that the internal business process perspective is too important and that internal owners or/and teams take ownership of understanding the process.

Learning and Growth Perspective

This perspective includes employee training and corporate cultural attitudes related to both individual and corporate self-improvement. In a knowledge-worker organization, people — the only repository of knowledge — are the main resource. In the current climate of rapid technological change, it is becoming necessary for knowledge workers to be in a continuous learning mode. Metrics can be put into place to guide managers in focusing training funds where they can help the most. In any case, learning and growth constitute the essential foundation for success of any knowledge-worker organization.

Kaplan and Norton emphasize that ‘learning’ is more than ‘training’; it also includes things like mentors and tutors within the organization, as well as that ease of communication among workers, the engagement of the workers, the potential of cross-training that would create pockets of bench strength and switch hitters, and other employee specific programs that allows them to readily get help on a problem when it is needed. It also includes technological tools; what the Baldrige criteria call “high performance work systems.”

Innovation Perspective

This perspective was appended to the above four by Bain and Company.  It refers to the vitality of the organization and its culture to provide the appropriate framework to encourage innovation. Organizations have to innovate. Innovation is becoming the key distinctive element in great organizations, and high levels of innovation or innovative thinking are talent magnets.

Taking the perspectives a step further, Kaplan and Cooper instituted measures and targets associated with each of those targets. The measures are geared around what the objective is associated with each of the perspectives rather than a singular granule item. Thus, if the objective is to increase customer retention, an appropriate metric or set of metrics is around how to measure the objective and track success to it than defining a customer.

One of the underlying presumptions in this model is to ensure that the key elements around which objectives are defined are done so at a fairly detailed level and to the extent possible – defined so much so that an item does not have polymorphous connotations. In other words, there is and can be only a single source of truth associated with the key element. That preserves the integrity of the model prior to its application that would lead to the element branching out into a plethora of objectives associated with the element.

Objectives, Measures, Targets and Initiatives

 

Within each of the Balance Scorecard financial, customer, internal process, learning perspectives and innovation perspectives, the firm must define the following:

Strategic Objectives – what the strategy is to achieve in that perspective

Measures – how progress for that particular objective will be measured

Targets – the target value sought for each measure

Initiatives – what will be done to facilitate the reaching of the target?

As in models and analytics, the information that the model spouts could be rife with a cascade of metrics. Metrics are important but too many metrics associated with the perspectives may diffuse the ultimate end that the perspectives represent.

Hence, one has to exercise restraint and rigor in defining a few key metrics that are most relevant and roll up to corporate objectives. As an example, outlined below are examples of metrics associated with the perspectives:

Financial performance (revenues, earnings, return on capital, cash flow);

Customer value performance (market share, customer satisfaction measures, customer loyalty);

Internal business process performance (productivity rates, quality measures, timeliness);

Employee performance (morale, knowledge, turnover, use of best demonstrated practices);

Innovation performance (percent of revenue from new products, employee suggestions, rate of improvement index);

To construct and implement a Balanced Scorecard, managers should:

  • Articulate the business’s vision and strategy;
  • Identify the performance categories that best link the business’s vision and strategy to its results (e.g., financial performance, operations, innovation, and employee performance);
  • Establish objectives that support the business’s vision and strategy;
  • Develop effective measures and meaningful standards, establishing both short-term milestones and long-term targets;
  • Ensure company wide acceptance of the measures;
  • Create appropriate budgeting, tracking, communication, and reward systems;
  • Collect and analyze performance data and compare actual results with desired performance;
  • Take action to close unfavorable gaps.

Source : http://www.ascendantsmg.com/blog/index.cfm/2011/6/1/Balanced-Scorecard-Strategy-Map-Templates-and-Examples

The link above contains a number of templates and examples that you may find helpful.

I have discussed organization architecture and employee engagement in our previous blogs. The BSC is a tool to encourage engagement while ensuring a tight architecture to further organizational goals. You may forget that as an employee, you occupy an important place in the ecosystem; the forgetting does not speak to your disenchantment toward the job, neither to your disinclination toward the uber-goals of the organization. The forgetting really speaks to potentially a lack of credible leadership that has not taken the appropriate efforts to engage the organization by pushing this structure that forces transparency. The BSC is one such articulate model that could be used, even at its crudest form factor, to get employees informed and engaged.

Viral Coefficient – Quick Study and Social Network Implications

Virality is a metric that has been borrowed from the field of epidemiology. It pertains to how quickly an element or content spreads through the population. Thus, these elements could be voluntarily or involuntarily adopted. Applying it to the world of digital content, I will restrict my scope to that of voluntary adoption by participants who have come into contact with the elements.

The two driving factors around virality relate to Viral Coefficient and Viral Cycle Time. They are mutually exclusive concepts, but once put together in a tight system within the context of product design for dissemination, it becomes a very powerful customer acquisition tool. However, this certainly does not mean that increased virality will lead to increased profits. We will touch upon this subject later on for in doing so we have to assess what profit means – in other words, the various components in the profit equation and whether virality has any consequence to the result. Introducing profit motive in a viral environment could, on the other hand, lead to counterfactual consequences and may depress the virality coefficient and entropy the network.

What is the Viral Coefficient?

You will often hear the Viral Coefficient referred to as K.  For example, you start an application that you put out on the web as a private beta. You offer them the tool to invite their contacts to register for the application. For example, if you start off with 10 private beta testers, and each of them invites 10 friends and let us say 20% of the 10 friends actually convert to be a registered user. What does this mean mathematically as we step through the first cycle?  Incrementally, that would mean 10*10*20% = 20 new users that will be generated by your initial ten users. So at the end of the first cycle, you would have 30 users. But bear in mind that this is the first cycle only. Now the 30 users have the Invite tool to send to 10 additional users of which 10% convert. What does that translate to?  It would be 30*10*10% =30 additional people over the base of 30 of your current installed based. That means now you have a total of 60 users. So you have essentially sent out 100 invites and then another 300 invites for a total of 400 invites — you have converted 50 users out of the 400 invites which translates to a 12.5% conversion rate through the second cycle. In general, you will find that as you step through more cycles, your conversion percentage will actually decay. In the first cycle, the viral coefficient (K) = 2 (Number of Invites (10) * conversion percentage (20%)), and through the incremental second cycle (K) = 10% (Number of Invites (10) * conversion percentage (10%)), and the total viral coefficient (K) is 1. If the K < 1, the system lends itself to decay … the pace of decay being a function of how low the viral coefficient is. On the other hand if you have K>1 or 100%, then your system will grow fairly quickly. The actual growth will be based on you starting base. A large starting base with K>1 is a fairly compelling model for growth.

The Viral Cycle Time:

This is the response time of a recipient to act upon an invite and send it out to their connection. In other words, using the above example, when your 10 users send out 10 invites and they are immediately acted upon ( for modeling simplicity, immediate means getting the invite and turning it around and send additional invites immediately and so on and on), that constitutes the velocity of the viral cycle otherwise known as Viral Cycle time. The growth and adoption of your product is a function of the viral cycle time. In other words, the longer the viral cycle time, the growth is significantly lower than a shorter viral cycle time.  For example if you reduce viral cycle time by ½, you may experience 100X+ growth. Thus, it is another important lever to manage the growth and adoption of the application.

 

 

So when one speaks of Virality, we have to consider the Virality Coefficient and the Viral Cycle Time. These are the key components and the drivers to these components may have dependencies, but there could be some mutually exclusive underlying value drivers. Virality hence must be built into the product. It is often common to think that marketing creates virality. I believe that marketing certainly does influence virality but it is more important, if and when possible, to design the product with the viral hooks.

 

 

Risk Management and Finance

If you are in finance, you are a risk manager. Say what? Risk management! Imagine being the hub in a spoke of functional areas, each of which is embedded with a risk pattern that can vary over time. A sound finance manager would be someone who would be best able to keep pulse, and be able to support the decisions that can contain the risk. Thus, value management becomes critical: Weighing the consequence of a decision against the risk that the decision poses. Not cost management, but value management. And to make value management more concrete, we turn to cash impact or rather – the discounted value of future stream of cash that may or may not be a consequent to a decision. Companies carry risks. If not, a company will not offer any premiums in value to the market. They create competitive advantage – defined as sorting a sustained growth in free cash flow as the key metric that becomes the separator.

John Kay, an eminent strategist, had identified four sources of competitive advantage: Organization Architecture and Culture, Reputation, Innovation and Strategic Assets. All of these are inextricably intertwined, and must be aligned to service value in the company. The business value approach underpins the interrelationships best. And in so doing, scenario planning emerges as a sound machination to manage risks. Understanding the profit impact of a strategy, and the capability/initiative tie-in is one of the most crucial conversations that a good finance manager could encourage in a company. Product, market and internal capabilities become the anchor points in evolving discussions. Scenario planning thus emerges in context of trends and uncertainties: a trend in patterns may open up possibilities, the latter being in the domain of uncertainty.

There are multiple methods one could use in building scenarios and engaging in fruitful risk assessment.
1.Sensitivity Assessment: Evaluate decisions in the context of the strategy’s reliance on the resilience of business conditions. Assess the various conditions in a scenario or mutually exclusive scenarios, assess a probabilistic guesstimate on success factors, and then offer simple solutions. This assessment tends to be heuristic oriented and excellent when one is dealing with few specific decisions to be made. There is an elevated sense of clarity with regard to the business conditions that may present itself. And this is most commonly used, but does not thwart the more realistic conditions where clarity is obfuscated and muddy.
2.Strategy Evaluation: Use scenarios to test a strategy by throwing a layer of interaction complexity. To the extent you can disaggregate the complexity, the evaluation of a strategy is better tenable. But once again, disaggregation has its downsides. We don’t operate in a vacuum. It is the aggregation, and negotiating through this aggregation effectively is where the real value is. You may have heard of the Mckinsey MECE (Mutually Exclusive; Comprehensively Exhaustive) methodology where strategic thrusts are disaggregated and contained within a narrow framework. The idea is that if one does that enough, one has an untrammeled confidence in choosing one initiative over another. That is true again in some cases, but my belief is that the world operates at a more synthetic level than pure analytic. We resort to analytics since it is too damned hard to synthesize, and be able to agree on an optimal solution. I am not creaming analytics; I am only suggesting that there is some possibility that a false hypothesis is accepted and a true one rejected. Thus analytics is an important tool, but must be weighed along with the synthetic tradition.
3.Synthetic Development: By far the most interesting and perhaps the most controversial with glint of academic and theoretical monstrosities included – this represents developing and broadcasting all scenarios equally weighed, and grouping interaction of scenarios. Thus, if introducing a multi-million dollar initiative in untested waters is a decision you have to weigh, one must go through the first two methods, and then review the final outcome against peripheral factors that were not introduced initially. A simple statement or realization like – The competition for Southwest is the Greyhound bus – could significantly alter the expanse of the strategy.

If you think of the new world of finance being nothing more than crunching numbers … stop and think again. Yes …crunching those numbers play a big part, less a cause than an effect of the mental model that you appropriate in this prized profession.